TextQuery is a web application that allows users to query CSV, JSON, and XLSX files using SQL. It simplifies data analysis by providing a familiar SQL interface to explore and filter data directly within the browser, eliminating the need for specialized software or complex scripting. Users can upload their files, write SQL queries against them, and instantly view the results in a tabular format. The service aims to be a quick and easy way to analyze structured data, particularly for those already comfortable with SQL.
A new web application called TextQuery has been launched, offering a streamlined way to query various text-based data formats, including CSV, JSON, XLSX, and delimited text files, using familiar SQL syntax. This tool aims to simplify the process of data exploration and analysis without requiring users to import their data into a traditional database system or write complex scripting code. The application boasts a user-friendly interface where users can directly paste their data, upload a file, or fetch data from a URL. Once the data is loaded, TextQuery automatically infers the schema, allowing users to immediately begin writing and executing SQL queries against the data. The results of the queries are then displayed in a clear, tabular format within the application. This eliminates the need for specialized software or extensive coding knowledge, making data analysis more accessible to a wider audience. TextQuery is positioned as a convenient tool for quick data exploration, ad-hoc analysis, and prototyping, particularly for tasks involving moderately sized datasets that don't necessitate the full capabilities of a dedicated database management system. It offers a lightweight and efficient solution for those seeking to leverage the power of SQL for simple data manipulation and retrieval directly within their web browser.
Summary of Comments ( 44 )
https://news.ycombinator.com/item?id=43897129
HN users generally expressed interest in TextQuery, praising its simplicity and potential usefulness for quick data analysis. Some compared it to other similar tools like
qandvisidata, suggesting TextQuery differentiates itself with a more approachable SQL interface beneficial for non-technical users. Several commenters brought up potential improvements, including support for larger files, more advanced SQL features like joins, and the ability to handle different delimiters in CSV files. One commenter highlighted the licensing model as a potential drawback, preferring a self-hosted or open-source option. Concerns about privacy and data security for cloud-based solutions were also raised.The Hacker News post for TextQuery, a tool for querying CSV, JSON, and XLSX files using SQL, has generated a moderate amount of discussion. Several commenters express interest and appreciation for the tool, finding the concept useful and well-executed.
One commenter points out the potential benefits of using a standard like SQL for querying various data formats, simplifying the process and eliminating the need to learn different tools or libraries for each format. They see this as a significant advantage, especially for those already familiar with SQL.
Another commenter praises the project's simplicity and ease of use, particularly highlighting the user-friendly web interface. They appreciate the ability to quickly load and query data without complex setup or configuration.
A few commenters raise questions about the project's underlying implementation and performance, specifically inquiring about the database used to process the queries. The creator clarifies that DuckDB is used, which is known for its efficiency in handling analytical queries.
There's also a discussion about potential use cases, with some commenters suggesting applications in data analysis, exploration, and transformation. One user specifically mentions using it for cleaning and preparing data for further processing.
A point of concern raised by one commenter is the lack of support for larger files, potentially limiting the tool's applicability in certain scenarios. However, the creator acknowledges this limitation and indicates plans for future improvements, including support for server-side processing to handle larger datasets.
Finally, several commenters express their intention to try out the tool, indicating a positive reception from the Hacker News community. Overall, the comments reflect a general appreciation for the project's concept, simplicity, and potential, while also acknowledging some areas for potential improvement.